BeamForge

An experimental text generation engine written in Rust from scratch. Instead of neural networks, BeamForge uses a stochastic semantic graph paired with a Beam Search algorithm. The goal is to explore what you can get from classical probabilistic methods with fast native tokenization and online learning.

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How it works

Tokenization: Raw text is converted to u32 identifiers. During generation the model works with integer arrays rather than strings, which keeps memory and CPU usage low.

Beam Search: Rather than greedy next-token selection, the algorithm explores multiple candidate sequences in parallel (BEAM_WIDTH = 5) and picks the globally highest-scoring completion. Scores are normalized by length to prevent the model from padding endlessly.

Online learning: Every declarative sentence typed by the user updates synaptic weights in real time. No training epochs, no restart.

Binary persistence: The brain state saves and loads via bincode. Fast enough to use between sessions.

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Internal architecture

The SemanticMesh brain uses three learning structures:

1. Trigrams (Synapses): w1 + w2 -> target. Strict two-word context to a third.
2. Bigrams (Fallback): w2 -> target. Used when the strict context is unknown.
3. Fast-Forward: Skips concepts to restart generation when user input is too short to match.

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Building

Requires Rust (stable).

Windows:

winget install --id Rustlang.Rustup -e
rustup default stable

Linux / macOS:

curl https://sh.rustup.rs -sSf | sh
source "$HOME/.cargo/env"

Run:

cargo run --bin beamforge

Release build:

cargo build --release --bin beamforge
# target/release/beamforge

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Usage

Once running, a YOU > prompt appears.

• Learning: type a normal sentence. The model integrates it into its weights instantly.
• Generation: end your input with ?. The model runs Beam Search and prints a response prefixed with BEAMFORGE:.

Commands:

Command	Effect
/train [folder]	Ingest all .txt and .md files in a folder
/save	Save the current brain to beamforge.brain
/load	Reload a previously saved brain
/quit	Exit

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Star History

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License

MIT.